Post-Baccalaureate Certificate of Machine Learning in Biomedical Sciences

Department of Computing

Unlock the power of machine learning to transform data into discoveries that advance human health and the life sciences.

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Machine Learning Training for Biological and Environmental Data

Machine learning is revolutionizing how researchers analyze complex data in the life sciences, enhancing everything from ecological modeling to molecular diagnostics, and from biodiversity tracking to genomic discovery.

The Post-Baccalaureate Certificate in Machine Learning for Life Sciences at Utah Tech University equips professionals and researchers with focused, project-based training in machine learning tools and techniques. No prior programming experience required.

PROGRAM TYPE

Post-Baccalaureate

OFFERED AS

Certificate

LEARNING TYPE

Online

COLLEGE

Science, Engineering, and Technology

Who Should Enroll

This certificate is ideal for professionals with a background in:

  • Biology, biochemistry, biotechnology, or environmental science
  • Molecular biology, genomics, pharmacology, or related disciplines
  • Any life sciences field where data plays a growing role in discovery and innovation

Program Outcomes

Graduates of this program will be able to:

  • Design computational approaches for biological data analysis
  • Apply machine learning techniques to solve real-world life science challenges
  • Visualize and interpret complex datasets to extract actionable insights
  • Communicate findings clearly to support data-driven decisions

Required Credits

Both of the following courses:

  • CS 6330
    • Programming for Machine Learning in Life Sciences
    • 3 Credits
  • CS 6342
    • Machine Learning for Life Sciences
    • 3 Credits

Optional Credits

Six credits from the courses below:

  • CS 6341
    • Machine Learning for Drug Discovery
    • 3 Credits
  • CS 6342
    • Machine Learning for Medical Imaging
    • 3 Credits
  • CS 6343
    • Machine Learning for Genomics, Transcriptomics, and Proteomics
    • 3 Credits
  • CS 6349R
    • Special Topics in Machine Learning for Life Sciences
    • *Available only with instructor approval
    • 1-3 Credits

$550 per Credit

Invest in a high-impact skillset without the burden of a full degree, while stretching your dollar further.

Total Credits: 12

Complete your certificate in less time and start applying machine learning in life sciences sooner.

Application Info

Requirements

Acceptance into the Certificate of Machine Learning Training for Biological and Environmental Data program will be based on the number of seats available and an evaluation of the following requirements:

  • Bachelor’s, Master’s, or Ph.D. in a life science or related field, with transcripts.
  • Resume/Curriculum vitae.

Resume/Curriculum Vitae

The resume/CV should provide the admissions committee with information about any experiences or skills you have supporting your candidacy for the Post-Baccalaureate Certificate in Machine Learning for Life Sciences. List your academic and professional work history, and any projects related to machine learning.

Process
  1. Apply through the main Utah Tech University Admissions Application at utahtech.edu/apply/
  2. Apply for graduate school through the Utah Tech University website by clicking on “Apply for Admissions” at the right-hand side of the main page or https://utahtech.edu/apply/
  3. Create an account if you are a first-time user, or log in if you attended UT in the past two years.
  4. On the new page, click on “Graduate Student Application (Master’s Degrees)” or “Start New Application”
  5. Fill out the appropriate year you plan to begin attending and fill everything out until the page gives you the chance to submit the following forms as a part of the application.
  6. Request official transcripts for all undergraduate and graduate coursework. Utah Tech/DSU undergraduates may request the registrar upload their transcript free of charge by emailing records@utahtech.edu.
  7. Upload required documents

Timeline

Deadlines

  • Preferred Admissions: Dec 5, 2025
  • Late Admissions: Jan 7, 2025

Start Date: Jan 12, 2026

What You’ll Gain

You’ll finish the program with a portfolio of applied ML projects aligned with current life sciences research and industry needs.

  • Practical coding skills using high-level programming languages and life science libraries
  • Working knowledge of common machine learning models used in biological data analysis

Hands-on Experience

Build and validate models for real-world applications such as:

  • Drug design and molecular screening
  • Genomic and proteomic data interpretation
  • Medical and biological image analysis

Getting Started

As a trailblazer in polytechnic education, we provide hands-on learning, cutting-edge technology, and real-world experience that prepares you for tomorrow’s challenges. Whether you’re aspiring to lead in engineering, business, or digital innovation, Utah Tech is where you’ll gain the skills and knowledge to push boundaries and redefine what’s possible.

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Contact

If you have any questions about this certificate and would like more information, reach out to Curtis Larsen (contact information can be found in this section).

Joe Francom

Department Chair, Computing

Email: joe.francom@utahtech.edu

Phone: (435) 652-7732

Office: BNO 237

Curtis Larsen, M.S.

Associate Professor of Computer Science

Email: Curtis.Larsen@utahtech.edu

Phone: (435) 652-7972

Office: HCC 463

Kevin Johnston

Assistant Professor

Email: Kevin.johnston@utahtech.edu

Phone: (435) 879-4258

Office: Snow 114A

Yuanfei "Steven" Sun, Ph.D.

Visiting Assistant Professor of the Practice in Machine Learning - Life Sciences

Email: Yuanfei.Sun@utahtech.edu

Phone: (435) 879-4285